EPE Association: EPE 2025 - LS5d: Control and electric drives

EPE 2025 - LS5d: Control and electric drives
You are here: EPE Documents > 01 - EPE & EPE ECCE Conference Proceedings > EPE 2025 - Conference > EPE 2025 - Topic 12: Electrical Machines and Drive Systems > EPE 2025 - LS5d: Control and electric drives

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   Direct Model-Based Predictive Torque Control with Variable Parameters for Induction Machines
By Qing CHEN, Yongdong LI, Jose RODRIGUEZ, Ralph KENNEL [View]
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Abstract: This paper presents several direct model-based predictive torque control (D-MPTC) approaches with variable parameters for induction machines (IM). The term 'variable parameters' specifically refers to the variable switching point and the variable weighting factor. Experimental results are provided to compare the strengths and limitations of each method.

   Drivetrain Loss Analysis for Various Switching Frequencies and Modulation Strategies Applied to IPMSMs
By Philipp TILLMANN, Daniel C. RODRIGUEZ PINTO, Martin NELL, Rolf LOEWENHERZ, Rik W. DE DONCKER [View]
[Download]

Abstract: This paper presents holistic loss simulations for round wire interior permanent magnet synchronous machines (IPMSMs) influenced by switching frequency and modulation strategy. Pulse width modulation (PWM) current waveforms, calculated with a precise nonlinear machine model, serve as input to a current-based finite element analysis (FEA) loss simulation in a two-step approach. Simulation and measurements align closely in test bench validations.

   Sensorless IPMSM Drive Enhanced with Parameter Identification Using Open-Loop Current Prediction Error and Gradients
By Aravinda PERERA, Roy NILSEN [View]
[Download]

Abstract: This article presents a position-sensorless Interior Permanent Magnet Synchronous Machine (IPMSM)drive scheme that incorporates an open-loop stator current predictor to identify electrical parameters and improve observer performance. Unlike classical observers, the proposed open-loop, full-order model is inherently sensitive to discrepancies between the physical and model parameters. Capitalizing on this sensitivity through current prediction error gradients (PEGs), the parameter estimator scheme identifies the temperature sensitive parameters, i.e., the permanent magnet flux linkage _m and stator resistance Rs. An offline experimental method, utilizing the sameprediction model, is proposed for mapping the inductance current relationship, which is subsequently implemented in the processor using a look-up table (LUT). Rotor position and speed are estimated via an Active Flux Observer, with real-time updates to all model parameters. Furthermore, a novel approach for tuning the estimation gain matrix using customized Hessian functions is presented, enabling improved simultaneous identification of _m and Rs. Experimental validation is conducted on a 3 kW IPMSM drive, with control and estimation routines implemented on a ZynqSystem-on-Chip (SoC)-based industrial embedded control platform. Results demonstrate that the proposed schemes enhance observer stability, precision, and robustness to parameter variations compared to conventional observers without parameter adaptation.

EPE 2025 - LS5d: Control and electric drives
You are here: EPE Documents > 01 - EPE & EPE ECCE Conference Proceedings > EPE 2025 - Conference > EPE 2025 - Topic 12: Electrical Machines and Drive Systems > EPE 2025 - LS5d: Control and electric drives
	[return to parent folder]

	Direct Model-Based Predictive Torque Control with Variable Parameters for Induction Machines By Qing CHEN, Yongdong LI, Jose RODRIGUEZ, Ralph KENNEL	[View] [Download]
Abstract: This paper presents several direct model-based predictive torque control (D-MPTC) approaches with variable parameters for induction machines (IM). The term 'variable parameters' specifically refers to the variable switching point and the variable weighting factor. Experimental results are provided to compare the strengths and limitations of each method.

	Drivetrain Loss Analysis for Various Switching Frequencies and Modulation Strategies Applied to IPMSMs By Philipp TILLMANN, Daniel C. RODRIGUEZ PINTO, Martin NELL, Rolf LOEWENHERZ, Rik W. DE DONCKER	[View] [Download]
Abstract: This paper presents holistic loss simulations for round wire interior permanent magnet synchronous machines (IPMSMs) influenced by switching frequency and modulation strategy. Pulse width modulation (PWM) current waveforms, calculated with a precise nonlinear machine model, serve as input to a current-based finite element analysis (FEA) loss simulation in a two-step approach. Simulation and measurements align closely in test bench validations.

	Sensorless IPMSM Drive Enhanced with Parameter Identification Using Open-Loop Current Prediction Error and Gradients By Aravinda PERERA, Roy NILSEN	[View] [Download]
Abstract: This article presents a position-sensorless Interior Permanent Magnet Synchronous Machine (IPMSM)drive scheme that incorporates an open-loop stator current predictor to identify electrical parameters and improve observer performance. Unlike classical observers, the proposed open-loop, full-order model is inherently sensitive to discrepancies between the physical and model parameters. Capitalizing on this sensitivity through current prediction error gradients (PEGs), the parameter estimator scheme identifies the temperature sensitive parameters, i.e., the permanent magnet flux linkage _m and stator resistance Rs. An offline experimental method, utilizing the sameprediction model, is proposed for mapping the inductance current relationship, which is subsequently implemented in the processor using a look-up table (LUT). Rotor position and speed are estimated via an Active Flux Observer, with real-time updates to all model parameters. Furthermore, a novel approach for tuning the estimation gain matrix using customized Hessian functions is presented, enabling improved simultaneous identification of _m and Rs. Experimental validation is conducted on a 3 kW IPMSM drive, with control and estimation routines implemented on a ZynqSystem-on-Chip (SoC)-based industrial embedded control platform. Results demonstrate that the proposed schemes enhance observer stability, precision, and robustness to parameter variations compared to conventional observers without parameter adaptation.